「querying」の検索結果

Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary testing.

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SQL discipline for querying Pulp Perfetto traces (.pftrace) with trace_processor — idempotent CREATE OR REPLACE PERFETTO views, GLOB not LIKE, dur = -1 incomplete-slice handling, EXTRACT_ARG for span args, joining on stable utid/upid, SPAN_JOIN PARTITIONED, and the draft→validate→execute loop. Ships Pulp's CPU/UI trace stdlib plus closed GPU startup, health, and probe views. TRIGGER when writing or debugging SQL over a .pftrace, when `pulp trace query` returns wrong/empty rows, or when the trace-analysis skill needs a query primitive.

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Use when building or maintaining a personal LLM-powered knowledge base. Triggers: ingesting sources into a wiki, querying wiki knowledge, linting wiki quality, 'add to wiki', 'what do I know about', or any mention of 'LLM wiki' or 'Karpathy wiki'.

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Assists in provisioning instances and databases, designing performant schemas, and querying data in Spanner. Use when designing primary keys, writing SQL queries or client library code, or diagnosing performance issues.

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Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs (including cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks.

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Discovers golden base images for creating GKE custom node images based on technical specifications or context clues. Use when finding the golden base image for custom GKE node creation, mapping cluster configuration parameters (GKE version, OS, architecture, accelerators, gVisor, cgroups) to image names, or querying GKE base image maps. Don't use for general GKE cluster creation (use gke-cluster-creation) or standard node pool management (use gke-basics).

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Answer natural language questions and perform analysis on GKE cluster and workload costs using BigQuery billing exports, cost allocation data, and live cluster monitoring metrics. Use when querying GKE costs across projects, namespaces, or workloads, analyzing billing reports in BigQuery (`bq`), checking cluster cost budgets (`gcloud billing`), or diagnosing cost drivers like pod requests vs. actual utilization (`kubectl top`). Don't use for applying cost optimization changes, creating rightsizing manifests (VPA/MPA), or selecting ComputeClasses (use gke-cost-optimization instead).

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Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly.

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Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for Bigtable, or diagnosing performance/hotspotting issues. Also use when provisioning Bigtable clusters using gcloud or cbt CLIs. Don't use for generic Cloud SQL administration.

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Operational setup guide for Salesforce Energy and Utilities Cloud: license activation, permission sets, industry-specific object configuration (ServicePoint, Meter, MeterReading, Consumption, ServiceAccount, ServiceContract, RatePlan), CIS/billing system integration, and service order management. NOT for generic admin setup, NOT for reading or querying the E&U data model schema (use architect/industries-data-model for that).

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Configure Einstein Activity Capture (EAC) for an org: enable the feature, create Configuration profiles, set auth type (User-Level or Org-Level OAuth), define email and calendar sync scope, excluded domains and privacy settings, assign users, verify sync health. NOT for querying synced emails or events in SOQL, Apex or reports — use apex/einstein-activity-capture-api. NOT for Opportunity Scoring or Pipeline Inspection — use agentforce/einstein-copilot-for-sales.

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Use this skill when configuring Health Cloud patient consent management: setting up HIPAA authorization forms, consent templates, consent tracking per patient, and withdrawal handling. NOT for querying the AuthorizationFormConsent object hierarchy or its required field values — use data/consent-data-model-health. NOT for GDPR/CCPA marketing opt-out on ContactPointTypeConsent — use security/gdpr-data-privacy.

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Programmatically driving Salesforce Approval Processes from Apex — `Approval.process(ProcessSubmitRequest)` to submit, `ProcessWorkitemRequest` to approve / reject / reassign, recall semantics, querying `ProcessInstance` and `ProcessInstanceWorkitem` to find pending approvals, and the bulk-submit / bulk-action error-row handling. Covers when to use Apex-driven approval (system-initiated submission, batch approvals, custom UIs) vs leaving the platform's standard buttons in place. NOT for the Approval Process metadata definition itself (that's admin / declarative — see admin/approval-processes), NOT for Flow-based approvals (use flow/flow-orchestration-patterns).

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Look up Microsoft API references, find working code samples, and verify SDK code is correct. Use when working with Azure SDKs, .NET libraries, or Microsoft APIs—to find the right method, check parameters, get working examples, or troubleshoot errors. Catches hallucinated methods, wrong signatures, and deprecated patterns by querying official docs.

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Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs, NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics.

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Manages the Morphir knowledge base under kb/ — OKF bundles and concept documents. Use when adding content to a bundle, creating a new bundle, checking the knowledge base for conformance or provenance drift, building or querying its SQLite index, managing intent through its lifecycle, recording or reading architectural decisions as Decision Records, or navigating, searching and listing its bundles, concepts and links.

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Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.

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法律事项的运营性计费执行。月度账单准备和计费指示、LC 发票审查和代垫款处理、客户账单质询回应、现金流建模（LC 付款义务与客户收款对比）、杠杆和消耗分析（人员配置组合、预测总成本、利润轨迹）。触发词：‘prepare the bill’（准备账单）、‘billing instruction’（计费指示）、‘end of month billing’（月末计费）、‘LC invoice’（LC 发票）、‘local counsel invoice’（本地顾问发票）、‘pass through as disbursement’（作为代垫款转付）、‘client querying the invoice’（客户质疑发票）、‘billing dispute’（计费争议）、‘cashflow gap’（现金流缺口）、‘when will we get paid’（我们何时能收到付款）、‘LC payment due’（LC 付款到期）、‘leverage analysis’（杠杆分析）、‘staffing mix’（人员配置组合）、‘predicted total cost’（预测总成本）、‘burn rate by grade’（按职级消耗率）、‘are we on track’（我们在轨道上吗）、‘what will this matter cost’（此事项将花费多少）。

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Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.

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Interactive Archon integration for knowledge base and project management via REST API. On first use, asks for Archon host URL. Use when searching documentation, managing projects/tasks, or querying indexed knowledge. Provides RAG-powered semantic search, website crawling, document upload, hierarchical project/task management, and document versioning. Always try Archon first for external documentation and knowledge retrieval before using other sources.

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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.

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Interact with Paddock — AI agent orchestration dashboard. Use when registering agents, managing tasks, syncing skills, or querying agent/task status via Paddock APIs.

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Bun runtime, package manager, bundler, and test runner. Use when running scripts with bun, managing packages, serving HTTP with Bun.serve, querying databases with Bun.sql/bun:sqlite/Bun.redis, shell scripting with $, using S3/file I/O, writing tests with bun:test, bundling or compiling to executable, or using any Bun-specific API (spawn, glob, semver, FFI, workers, plugins, HTMLRewriter).

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